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Findings show consistent, substantial positive impacts on learning outcomes, with an overall pooled effect size of 0.37 SD, stronger effects for teacher/paraprofessional tutoring and earlier grades.",{"@graph":14,"@context":73},[15,34,56],{"@type":16,"itemListElement":17},"BreadcrumbList",[18,23,27,31],{"item":19,"name":20,"@type":21,"position":22},"https://docshare.wps.com","Home","ListItem",1,{"item":24,"name":25,"@type":21,"position":26},"https://docshare.wps.com/document/","Document",2,{"item":28,"name":29,"@type":21,"position":30},"https://docshare.wps.com/document/research-report/","Research & 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of the Experimental Evidence  \nAndre Joshua Nickow  \nNorthwestern University  \nPhilip Oreopoulos  \nUniversity of Toronto  \nVincent Quan  \nJ-PAL North America  \nTutoring—defined here as one-on-one or small-group instructional programming by teachers, paraprofessionals, volunteers, or parents—is one of the most versatile and potentially transformative educational tools in use today. Within the past decade, dozens of preK-12 tutoring experiments have been conducted, varying widely in their approach, context, and cost. Our study represents the first systematic review and meta-analysis of these and earlier studies. We develop a framework for considering different types of programs to not only examine overall effects, but also explore how these effects vary by program characteristics and intervention context. We find that tutoring programs yield consistent and substantial positive impacts on learning outcomes, with an overall pooled effect size estimate of 0.37 SD. Effects are stronger, on average, for teacher and paraprofessional tutoring programs than for nonprofessional and parent tutoring. Effects also tend to be strongest among the earlier grades. While overall effects for reading and math interventions are similar, reading tutoring tends to yield higher effect sizes in earlier grades, while math tutoring tends to yield higher effect sizes in later grades. Tutoring programs conducted during school tend to have larger impacts than those conducted after school.  \nVERSION: July 2020  \nSuggested citation: Nickow, Andre Joshua, Philip Oreopoulos, and Vincent Quan. (2020). The Impressive Effects of Tutoring on PreK-12 Learning: A Systematic Review and Meta-Analysis of the Experimental Evidence.(EdWorkingPaper: 20-267). Retrieved from Annenberg Institute at Brown University:  \n[https://doi.org/10.26300/eh0c-pc52](https://doi.org/10.26300/eh0c-pc52)  \nThe Impressive Effects of Tutoring on PreK-12 Learning: A Systematic Review and Meta-Analysis of the Experimental Evidence  \nAndre Joshua Nickow, Northwestern University  \n[a-nickow@kellogg.northwestern.edu](a-nickow@kellogg.northwestern.edu)  \nPhilip Oreopoulos, University of Toronto, NBER, J-PAL North America  \n[philip.oreopoulos@utoronto.ca](philip.oreopoulos@utoronto.ca)  \n[Vincent Quan](Vincent Quan), J-PAL North America  \n[vquan@povertyactionlab.org](vquan@povertyactionlab.org)  \nAbstract: Tutoring—defined here as one-on-one or small-group instructional programming by teachers, paraprofessionals, volunteers, or parents—is one of the most versatile and potentially transformative educational tools in use today. Within the past decade, dozens of preK-12 tutoring experiments have been conducted, varying widely in their approach, context, and cost. Our study represents the first systematic review and meta-analysis of these and earlier studies. We develop a framework for considering different types of programs to not only examine overall effects, but also explore how these effects vary by program characteristics and intervention context. We find that tutoring programs yield consistent and substantial positive impacts on learning outcomes, with an overall pooled effect size estimate of 0.37 SD. Effects are stronger, on average, for teacher and paraprofessional tutoring programs than for nonprofessional and parent tutoring. Effects also tend to be strongest among the earlier grades. While overall effects for reading and math interventions are similar, reading tutoring tends to yield higher effect sizes in earlier grades, while math tutoring tends to yield higher effect sizes in later grades. Tutoring programs conducted during school tend to have larger impacts than those conducted after school.  \nAcknowledgements: We would like to thank Kimberly Dadisman for her invaluable work in moving the project forward, Bradley Clark for his excellent research assistance, and Jonath","cbCainUATQRLaxPj","https://ap.wps.com/l/cbCainUATQRLaxPj","pdf",805887,84,"English","# Abstract\n# Introduction\n## Tutoring interventions and their growth\n## Evidence history and the “2 sigma problem\"","[{\"question\":\"How does the study define tutoring in preK-12 learning research?\",\"answer\":\"Tutoring is defined as one-on-one or small-group instructional programming delivered by teachers, paraprofessionals, volunteers, or parents.\"},{\"question\":\"What is the overall estimated impact of tutoring on learning outcomes?\",\"answer\":\"Tutoring yields consistent and substantial positive impacts, with an overall pooled effect size estimate of 0.37 SD.\"},{\"question\":\"What factors influence how strong tutoring effects are?\",\"answer\":\"Effects are stronger on average for teacher and paraprofessional tutoring than for nonprofessional and parent tutoring, tend to be strongest in earlier grades, and tend to be larger for programs conducted during school than after school.\"}]","The Impressive Effects of Tutoring on PreK-12 Learning - A Systematic Review and Meta-Analysis of the Experimental Evidence | PDF",1790397217,212]